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Record W7054800026

Avaliação do crossmatch por citometria de fluxo

2021· dissertation· pt· W7054800026 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Repository of the Polytechnic Institute of Porto (Polytechnic Institute of Porto) · 2021
Typedissertation
Languagept
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHolliday junctionStatistical analysisBlood donor
DOInot available

Abstract

fetched live from OpenAlex

O estágio realizou-se no serviço de transplantação do Centro de Sangue e Transplantação de Coimbra, que permitiu adquirir competências a nível das provas de crossmatch. O crossmatch anti-linfocitário consiste no ensaio padrão utilizado na área da transplantação que permite avaliar a compatibilidade HLA entre um dador e um recetor, prevenindo a rejeição do aloenxerto mediada por anticorpos. A metodologia atual fornece informações sobre o risco da realização de um transplante, melhorando as taxas de aceitação do enxerto alogénico. No entanto, existem limitações na distinção de padrões de reatividade durante o processo de crossmatch por citometria de fluxo, considerando ligações não específicas que conduzem a resultados inexactos que impedem consequentemente o transplante. Desta forma, com os aanços no campo da imuno-histocompatibilidade, têm sido induzidas atualizações no procedimento das provas cruzadas, como o Halifaxe e Halifaster, que possibilitam melhorar os resultados obtidos. Para este projeto foram propostos métodos adaptados ao serviço, com o objetivo de comparar a sensibilidade e especificidade entre os protocolos de crossmatch e investigar a significância clínica na compatibilidade linfocitária entre dadores e recetores. A análise dos casos estudados revelou melhorias na utilização do protocolo Halifax estipulado comparando com o Standard para as classes HLA, especialmente para a classe II.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.262
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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